Saturday, December 31, 2011

MongoDB, as some of you may know, has a process-wide write lock. This has caused some degree of ridicule from database purists when they discover such a primitive locking model. Now per-database and per-collection locking is on the roadmap for MongoDB, but it's not here yet. What was announced in MongoDB version 2.0 was locking-with-yield. I was curious about the performance impact of the write lock and the improvement of lock-with-yield, so I decided to do a little benchmark, MongoDB 1.8 versus MongoDB 2.0.

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Useful Resources

Interested in practical MongoDB programming?

MongoDB Applied Design Patternsis available now, both in ebook and dead-tree form. In it, you'll see how to use MongoDB effectively in fields from real-time analytics to content management systems and more. The examples are all in Python, so readers of this blog should have no problem picking it all up.

Want to learn MongoDB using Python?

I just released an 84-page ebook MongoDB with Python and Ming to help you get started. In it, I cover everything from installing MongoDB for the first time, basic pymongo usage, MongoDB aggregation including MapReduce and the new aggregation framework, and GridFS. You'll also learn about Ming, the object-document mapper we built at SourceForge to accelerate our development beyond what we could do with PyMongo.

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I'm collecting a list of products and services I've found useful in my work & leisure Python programming at Rick's Resources. If you're interested in that sort of thing, I'd love to have you check it out!